Stochastic Transition Systems for Continuous State Spaces and Non-determinism

Appears: Proceedings of the 8th International Conference on Foundations of Software Science and Computational Structures (FOSSACS), Edinburgh, UK, LNCS 3441, pages 125--139, April 2005.

Abstract: We study the interaction between non-deterministic and probabilistic behaviour in systems with continuous state spaces, arbitrary probability distributions and uncountable branching. Models of such systems have been proposed previously. Here, we introduce a model that extends probabilistic automata to the continuous setting. We identify the class of schedulers that ensures measurability properties on executions, and show that such measurability properties are preserved by parallel composition. Finally, we demonstrate how these results allow us to define an alternative notion of weak bisimulation in our model.

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